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      "9.916002163802123 [1.59868211 0.38111511] [1.52662322 0.33446563] [1.36835491 0.29793856]\n",
      "12.409547158848543 [1.         0.31865139] [1.         0.29673575] [1.         0.25524303]\n",
      "12.575131449327872 [1.54827206 0.1353389 ] [1.45397267 0.13495303] [1.412522   0.09243483]\n",
      "10.047461271617449 [1.         0.13838947] [1.         0.12543906] [1.07980201 0.03699989]\n",
      "11.168585162085147 [1.40165996 0.36333975] [1.22556733 0.34348119] [1.03948977 0.30648717]\n",
      "6.3148142448845785 [1.05192976 0.21690696] [1.04212699 0.17886409] [1.00050678 0.14293561]\n",
      "4.213174439921227 [1.03662484 0.28966567] [1.00215127 0.26474702] [1.         0.21927834]\n",
      "9.350377743405199 [1.         0.35654214] [1.         0.32229306] [1.         0.27400208]\n",
      "7.092296103190132 [1.03188979 0.36834402] [1.05524235 0.32111044] [1.         0.29487285]\n",
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      "8.949140629837553 [1.05108868 0.39110188] [1.         0.36651523] [1.         0.30836115]\n",
      "8.716553166271584 [1.         0.14921731] [1.        0.1269959] [1.        0.1051833]\n",
      "10.086518745680003 [1.69681287 0.04678019] [1.12508498 0.24327165] [1.         0.33185283]\n",
      "11.182964161467057 [1.63311972 0.42401394] [1.38102156 0.42183174] [1.22833146 0.39035724]\n",
      "13.76180563173197 [1.        0.3762183] [1.         0.34865231] [1.         0.30293159]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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    },
    {
     "name": "stdout",
     "output_type": "stream",
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      "9.594943678759213 [1.         0.42423773] [1.         0.38552999] [1.         0.32468429]\n",
      "5.3791976022018515 [1.54201572 0.06628701] [1.40167858 0.07165457] [1.2690287  0.06592292]\n",
      "19.77399570300559 [1.07824599 0.38281923] [1.00398616 0.36607595] [1.1181896  0.23795898]\n",
      "9.580546761468955 [1.37306584 0.17577431] [1.30179416 0.16933436] [1.21704513 0.14663145]\n",
      "13.33828004159378 [1.         0.36330007] [1.         0.30110656] [1.07022844 0.1971349 ]\n",
      "7.26545664572203 [1.00320889 0.27332249] [1.08149899 0.20519183] [1.13360372 0.12610142]\n",
      "4.020766820685916 [1.84646009 0.34098613] [1.67902187 0.29709569] [1.24429486 0.27404391]\n",
      "19.273838139796524 [1.23985283 0.15511182] [1.07159674 0.18082891] [1.38035117 0.04312197]\n",
      "18.747154847936542 [1.2879973  0.17396842] [1.02469479 0.2312224 ] [1.38216191 0.04543679]\n",
      "7.687501494777646 [1.18911408 0.13068791] [1.21358109 0.10652954] [1.1600769  0.11167813]\n",
      "17.41626227161925 [1.24286567 0.17648605] [1.         0.23681838] [1.37625362 0.04062536]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4.608339372745333 [1.74113426 0.34798842] [1.52317166 0.3191022 ] [1.16724291 0.2942582 ]\n",
      "18.875741071133284 [1.2543283  0.15648117] [1.06798541 0.18717109] [1.34530144 0.04991616]\n",
      "11.148313150594289 [1.         0.37511565] [1.09509921 0.28287656] [1.14942929 0.17369543]\n",
      "7.233035561460236 [1.08561326 0.2354706 ] [1.20422952 0.14769201] [1.1853493  0.09605807]\n",
      "8.863229059881018 [1.41297349 0.19649819] [1.33371269 0.18662474] [1.22792143 0.15976778]\n",
      "19.45745868435802 [1.49994807 0.26682565] [1.26711735 0.27545718] [1.34188963 0.14555973]\n",
      "9.468170012731786 [1.         0.42522692] [1.         0.38323518] [1.         0.32367061]\n",
      "5.868515168416221 [1.52897243 0.06848402] [1.38364141 0.07468658] [1.25120255 0.06850521]\n",
      "6.000131214338976 [1.         0.12002132] [1.        0.0980278] [1.0169329  0.05973255]\n",
      "7.438143572576681 [1.         0.28502836] [1.         0.26303692] [1.         0.22860402]\n",
      "5.289794627964023 [1.1335567  0.21179734] [1.11170322 0.19507687] [1.07163701 0.16266489]\n",
      "7.964680770390557 [1.14781153 0.42575943] [1.         0.40190126] [1.         0.33838822]\n",
      "10.032075253179388 [1.19303526 0.34074064] [1.17790367 0.30367674] [1.13926281 0.24261738]\n",
      "9.507332791209954 [1.         0.36297141] [1.12549776 0.27003628] [1.00850659 0.26411807]\n",
      "2.819872748989664 [1.         0.23983558] [1.        0.2266287] [1.        0.1979991]\n",
      "7.495457263473503 [1.23996667 0.23219605] [1.25828273 0.17540812] [1.2256135  0.09706519]\n",
      "3.3035183593098116 [1.05401011 0.0786346 ] [1.0064354 0.0834124] [1.00066125 0.06275393]\n",
      "10.982202783668944 [1.01541626 0.32391523] [1.04335354 0.26363175] [1.02417349 0.21390277]\n",
      "5.444681012424603 [1.21112693 0.34450231] [1.49266707 0.19883686] [1.21760034 0.16245562]\n",
      "5.71585520980478 [1.38514994 0.07153152] [1.26599542 0.07115983] [1.28125242 0.00203232]\n",
      "4.78489739965205 [1.42650945 0.09035256] [1.35666958 0.08265567] [1.25431092 0.05747103]\n",
      "9.338768434828841 [1.28952457 0.20208728] [1.12484015 0.21011617] [1.14263045 0.1109362 ]\n",
      "6.073680103146996 [1.00675102 0.26630249] [1.02387754 0.23440817] [1.02017898 0.1963962 ]\n",
      "8.881113087703643 [1.         0.39147761] [1.13747849 0.30262937] [1.13791602 0.21990965]\n",
      "6.288096344683792 [1.22002553 0.34162078] [1.05898669 0.32589906] [1.         0.28077121]\n",
      "6.370692375869698 [1.47119504 0.02273981] [1.14891519 0.14920475] [1.        0.2303363]\n",
      "7.1979636175223405 [1.11389871 0.23466379] [1.10305907 0.20912161] [1.06224552 0.16659362]\n",
      "5.849074255529509 [1.         0.24786564] [1.         0.22290166] [1.         0.18581435]\n",
      "3.6782213024410426 [1.54906327 0.38499582] [1.38170487 0.35972071] [1.05013607 0.33461307]\n",
      "4.76170856930791 [1.13572491 0.38745464] [1.03104303 0.37008839] [1.         0.32496164]\n",
      "5.155595609262272 [1.         0.49398408] [1.         0.46194917] [1.         0.41697888]\n",
      "6.642882304921422 [1.59828797 0.1202163 ] [1.4459217  0.11160453] [1.19351043 0.12236486]\n",
      "4.814149145007596 [1.06481287 0.11952267] [1.08056103 0.08142804] [1.04100738 0.05845668]\n",
      "5.019245705742924 [1.08739817 0.26074022] [1.06015233 0.22453726] [1.08866459 0.14105046]\n",
      "9.16744872104858 [1.23419148 0.43999962] [1.20295263 0.398843  ] [1.098967   0.34742564]\n",
      "4.786575682308314 [1.         0.28540823] [1.         0.27403455] [1.         0.18088439]\n",
      "8.250491528487505 [1.         0.39301486] [1.         0.34821779] [1.         0.27898305]\n",
      "8.866099271504389\n"
     ]
    }
   ],
   "source": [
    "import cv2\n",
    "import os\n",
    "from os import listdir\n",
    "from os.path import isfile, join\n",
    "from PIL import Image as Image\n",
    "import numpy as np\n",
    "\n",
    "from scipy.optimize import curve_fit\n",
    "\n",
    "def relit(x, a, b):\n",
    "    return (a * x.astype(np.float)/255 + b)*255\n",
    "\n",
    "\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "def plshow(im,title='MINE'):\n",
    "    if len(im.shape)>2:\n",
    "  #      plt.imshow(cv2.cvtColor(im, cv2.COLOR_BGR2RGB))\n",
    "        plt.imshow(im)\n",
    "    else:\n",
    "        plt.imshow(im,cmap='gray')\n",
    "    plt.title(title)\n",
    "    plt.rcParams[\"figure.figsize\"] = (80,12)\n",
    "    plt.show()\n",
    "\n",
    "sd_path = 'dataset/ISTD/train_A'\n",
    "mask_path = 'dataset/ISTD/train_B'\n",
    "sdfree_path = 'dataset/ISTD/train_C_fixed_ours'\n",
    "\n",
    "out = 'dataset/ISTD/train_params/'\n",
    "if not os.path.exists(out):\n",
    "    os.makedirs(out)\n",
    "\n",
    "im_list  =  [f for f in listdir(sd_path) if isfile(join(sd_path, f)) and f.endswith('png')]\n",
    "print(len(im_list),im_list[0])\n",
    "kernel = np.ones((5,5),np.uint8)\n",
    "\n",
    "\n",
    "def im_relit(Rpopt,Gpopt,Bpopt,dump):\n",
    "    #fc this shit\n",
    "    sdim = dump.copy()\n",
    "    sdim.setflags(write=1)\n",
    "    sdim = sdim.astype(np.float)\n",
    "    sdim[:,:,0] = (sdim[:,:,0]/255) * Rpopt[0] + Rpopt[1]\n",
    "    sdim[:,:,1] = (sdim[:,:,1]/255) * Gpopt[0] + Gpopt[1]\n",
    "    sdim[:,:,2] = (sdim[:,:,2]/255) * Bpopt[0] + Bpopt[1]\n",
    "    sdim = sdim*255\n",
    "   # print(np.amin(sdim),np.amax(sdim))\n",
    "    return sdim\n",
    "\n",
    "errors= []\n",
    "for im in im_list:\n",
    "    sd = np.asarray(Image.open(join(sd_path,im)))\n",
    "    mean_sdim = np.mean(sd,axis=2)\n",
    "    \n",
    "    mask_ori = np.asarray(Image.open(join(mask_path,im)))\n",
    "    mask = cv2.erode(mask_ori ,kernel,iterations = 2)\n",
    "\n",
    "    \n",
    "    sdfree = np.asarray(Image.open(join(sdfree_path,im)))\n",
    "    mean_sdfreeim = np.mean(sdfree,axis=2)\n",
    "    \n",
    "    #pixels for regression funtion\n",
    "    i, j = np.where(np.logical_and(np.logical_and(np.logical_and(mask>=1,mean_sdim>5),mean_sdfreeim<230),np.abs(mean_sdim-mean_sdfreeim)>10))\n",
    "\n",
    "    source = sd*0\n",
    "    source[tuple([i,j])] = sd[tuple([i,j])] \n",
    "    target = sd*0\n",
    "    target[tuple([i,j])]= sdfree[tuple([i,j])]\n",
    "    \n",
    "    R_s = source[:,:,0][tuple([i,j])]\n",
    "    G_s = source[:,:,1][tuple([i,j])]\n",
    "    B_s = source[:,:,2][tuple([i,j])]\n",
    "    \n",
    "    R_t = target[:,:,0][tuple([i,j])]\n",
    "    G_t = target[:,:,1][tuple([i,j])]\n",
    "    B_t = target[:,:,2][tuple([i,j])]\n",
    "    \n",
    "    c_bounds = [[1,-0.1],[10,0.5]]\n",
    "\n",
    "    \n",
    "    Rpopt, pcov = curve_fit(relit, R_s, R_t,bounds=c_bounds)\n",
    "    Gpopt, pcov = curve_fit(relit, G_s, G_t,bounds=c_bounds)\n",
    "    Bpopt, pcov = curve_fit(relit, B_s, B_t,bounds=c_bounds)\n",
    "    \n",
    "    \n",
    "    relitim = im_relit(Rpopt,Gpopt,Bpopt,sd)\n",
    "    \n",
    "    #final = sd.copy()\n",
    "    #final[tuple([i,j])] = relitim[tuple([i,j])]\n",
    "    #final[final>255] =255\n",
    "    #final[final<0] = 0\n",
    "\n",
    "    #plshow(final)\n",
    "    error = np.mean(np.abs(relitim[tuple([i,j])].astype(np.float) - sdfree[tuple([i,j])]).astype(np.float))\n",
    "    print(error,Rpopt,Gpopt,Bpopt)\n",
    "    f = open(join(out,im+'.txt'),\"a\")\n",
    "    f.write(\"%f %f %f %f %f %f\"%(Rpopt[1],Rpopt[0],Gpopt[1],Gpopt[0],Bpopt[1],Bpopt[0]))\n",
    "    f.close()\n",
    "             \n",
    "  #  print(error)\n",
    "    errors.append(error)\n",
    "                    \n",
    "    \n",
    "print(np.mean(errors))\n",
    "#no bound - 8.55\n",
    "#### y_bound ###error\n",
    "#    0.5        8.86\n",
    "#    0.1        15.692271753155671    \n",
    "#    0.25       10.830443545867785\n",
    "#    1          8.86"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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